• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.129-140
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• 2023

Autonomous driving systems are likely to be operated in various complex environments. However, the well-known integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), which is currently the major source for absolute position information, still has difficulties in accurate positioning in harsh signal environments such as urban canyons. To overcome these difficulties, integrated Visual/Inertial/GNSS (VIG) navigation systems have been extensively studied in various areas. Recently, a Compressed-State Constraint Kalman Filter (CSCKF)-based VIG navigation system (CSCKF-VIG) using a monocular camera, an Inertial Measurement Unit (IMU), and GNSS receivers has been studied with the aim of providing robust and accurate position information in urban areas. For this new filter-based navigation system, on the basis of time-propagation measurement fusion theory, unnecessary camera states are not required in the system state. This paper presents a performance evaluation of the CSCKF-VIG system compared to other conventional navigation systems. First, the CSCKF-VIG is introduced in detail compared to the well-known Multi-State Constraint Kalman Filter (MSCKF). The CSCKF-VIG system is then evaluated by a field experiment in different GNSS availability situations. The results show that accuracy is improved in the GNSS-degraded environment compared to that of the conventional systems.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.2
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• pp.189-197
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• 2024

Galileo is a European Global Navigation Satellite System (GNSS) that has offered the Galileo Open Service since 2016. Consequently, the standardization of GNSS augmentation systems, such as Satellite Based Augmentation System (SBAS), Ground Based Augmentation System (GBAS), and Aircraft Based Augmentation System (ABAS) for Galileo signals, is ongoing. In 2023, the European Union Space Programme Agency (EUSPA) released prior probabilities of a satellite fault and a constellation fault for Galileo, which are 3×10^-5 and 2×10^-4 per hour, respectively. In particular, the prior probability of a Galileo constellation fault is significantly higher than that for the GPS constellation fault, which is defined as 1×10^-8 per hour. This raised concerns about its potential impact on GBAS integrity monitoring. According to the Global Positioning System (GPS) Standard Positioning Service Performance Standard (SPS PS), a constellation fault is classified as a wide fault. A wide fault refers to a fault that affects more than two satellites due to a common cause. Such a fault can be caused by a failure in the Earth Orientation Parameter (EOP). The EOP is used when transforming the inertial axis, on which the orbit determination is based, to Earth Centered Earth Fixed (ECEF) axis, accounting for the irregularities in the rotation of the Earth. Therefore, a faulty EOP can introduce errors when computing a satellite position with respect to the ECEF axis. In GNSS, the ephemeris parameters are estimated based on the positions of satellites and are transmitted to navigation satellites. Subsequently, these ephemeris parameters are broadcasted via the navigation message to users. Therefore, a faulty EOP results in erroneous broadcast ephemeris data. In this paper, we assess the conventional ephemeris fault detection monitor currently employed in GBAS for wide faults, as current GBAS considers only single failure cases. In addition to the existing requirements defined in the standards on the Probability of Missed Detection (PMD), we derive a new PMD requirement tailored for a wide fault. The compliance of the current ephemeris monitor to the derived requirement is evaluated through a simulation. Our findings confirm that the conventional monitor meets the requirement even for wide fault scenarios.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.335-340
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• 2021

A constant envelope multiplexing via constellation tailoring scheme is proposed for flexible power allocation of Global Navigation Satellite System (GNSS) signals. The proposed scheme is compared with the coherent adaptive subcarrier modulation (CASM) adopted in the L1 band signals of the Global Positioning System (GPS) in terms of power difference and power loss. Analysis of the constellation optimization results on the power difference and power loss show that the proposed scheme outperforms the CASM of the GPS signals in the allowable power difference of less than 0.1 dB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1619-1625
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• 2017

Civil global navigation satellite system (GNSS) does not meet user performance requirements for specific PNT (Positioning, Navigation, and Time) applications. Therefore, various differential systems are used to augment GNSS for improving positioning accuracy and integrity. The MTSAT satellite augmentation system (MSAS) is the Japanese satellite based augmentation system. This paper is for analyzing the characteristics of Japanese MSAS in Korean peninsula. First of all, it was done for analyzing not only DGNSS navigation signal but also the navigation parameter through simulation and experimental tests. As a result of data analyses, the sufficient navigation satellites to determine 3-D position based on DGNSS are simultaneously available at MSAS monitering station and the southern region of Korean peninsula. It was verified that the carrier to noise signals are stable to maintain the reliable 3-D position and that the level of 2m (2drms) accuracy is very similar to the ordinary worldwide DGNSS as well.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.23-28
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• 2021

Data analysis research using deep learning has recently been studied in various field. In this paper, we conduct a GNSS (Global Navigation Satellite System)-based meteorological study applying deep learning by estimating the ZWD (Zenith tropospheric Wet Delay) through MLP (Multi-Layer Perceptron) and LSTM (Long Short-Term Memory) models. Deep learning models were trained with meteorological data and ZWD which is estimated using zenith tropospheric total delay and dry delay. We apply meteorological data not used for learning to the learned model to estimate ZWD with centimeter-level RMSE (Root Mean Square Error) in both models. It is necessary to analyze the GNSS data from coastal areas together and increase time resolution in order to estimate ZWD in various situations.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.51-58
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• 2023

Geofencing supports unmanned aerial vehicle (UAV) operation by defining stay-in and stay-out regions. National Aeronautics and Space Administration (NASA) has developed a prototype of the geofencing function, SAFEGUARD, which prevents stayout region violation by utilizing position estimates. Thus, SAFEGUARD depends on navigation system performance, and the safety risk associated with the navigation system uncertainty should be considered. This study presents a methodology to compute the safety risk assessment-based along-track position error bound under nominal and Global Navigation Satellite Systems (GNSS) failure conditions. A Kalman filter system using pseudorange measurements as well as pseudorange rate measurements is considered for determining the position uncertainty induced by velocity uncertainty. The worst case pseudorange and pseudorange rate fault-based position error bound under the GNSS failure condition are derived by applying a Receiver Autonomous Integrity Monitor (RAIM). Position error bound simulations are also conducted for different GNSS fault hypotheses and constellation conditions with a GNSS/INS integrated navigation system. The results show that the proposed along-track position error bounds depend on satellite geometries caused by UAV attitude change and are reduced to about 40% of those of the single constellation case when using the dual constellation.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.87-94
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• 2019

The Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) positioning has been widely used in geodesy, surveying, and navigation fields. RTK can benefit enormously from the integration of multi-GNSS. In this study, we develop a GPS/BeiDou Navigation Satellite System (BDS) RTK integration algorithm for long baselines ranging from 128 km to 335 km in South Korea. The positioning performance with GPS/BDS RTK, GPS-only RTK, and BDS-only RTK is compared in terms of the positioning accuracy. An improvement of positioning accuracy over long baselines can be found with GPS/BDS RTK compared with that of GPS-only RTK and that of BDS-only RTK. The positioning accuracy of GPS/BDS RTK is better than 2 cm in the horizontal direction and better than 5 cm in the vertical direction. A lower Relative Dilution of Precision (RDOP) value with GPS/BDS integration can obtain a better positional precision for long baseline RTK positioning.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.3
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• pp.183-188
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• 2018

The Global Navigation Satellite System (GNSS) signal gets delayed as it goes through the troposphere before reaching the GNSS antenna. Various tropospheric models are being used to correct the tropospheric delay. In this study, we compared effectiveness of two popular troposphere correction models: Global Pressure and Temperature (GPT) and Satellite-Based Augmentation System (SBAS). One-year data from a particular site was chosen as the test case. Tropospheric delays were computed using the GPT and SBAS models and compared with the International GNSS Service tropospheric product. The bias of SBAS model computations was 3.4 cm, which is four times lower than that of the GPT model. The cause of higher biases observed in the GPT model is the fact that one cannot get wet delays from the model. If SBAS-based wet delays are added to the hydrostatic delays computed using the GPT model, then the accuracy is similar to that of the full SBAS model. From this study, one can conclude that it is better to use the SBAS model than to use the GPT model in the standard code-pseudorange data processing.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.499-506
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• 2015

Global navigation satellite systems (GNSS) is operating widely in civil and military area. GNSS signals, however, can be easily interfered because its signal is vulnerable to jamming. Thus, a sort of backup or alternative system is needed in order that the navigation performance is assured to a certain degree in case of GNSS jamming. In order to suggest a series of backup or alternative system of regional navigation, in this paper, we introduced a high altitude long endurance unmanned aerial vehicle (HALE UAV) with pseudolites using inverted GPS and transceiver system. We simulated the positioning error of the regional navigation system using HALE UAV with inverted GPS or transceivers concepts. We estimated the position error of HALE UAV calculate user position errors based on the position error of HALE UAV and general pseudorange error.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1588-1595
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• 2021

Android-based smartphones receive the global navigation satellite system (GNSS) signals to determine their location and provide the GNSS raw measurement to users. The available GNSS signals on the current Android devices are GPS, GLONASS, Galileo, BeiDou, QZSS. This research has analyzed the performance of multi-GNSS position accuracy based on the pseudorange of the smartphone for maritime users. Smartphones capable of receiving dual-frequency are installed on a ship, and multi-GNSS raw information in maritime environment was measured to present the results of comparing the GNSS pseudorange-based dual-frequency positioning performance for each smarphone. Furthermore, we analyzed whether the results of the positioning performance can meet the HEA requirement of IMO for maritime navigation users. As the results of maritime experiment, it was confirmed that in the case of the smartphones supporting the dual-frequency, the position accuracy within 6 meters (95%) could be obtained, and the HEA position accuracy performance within 10 meters (95%) required by IMO could be achieved.